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Phil Steitz commented on MATH878:

Implementation code committed in r1405620.
I made no material changes  just javadoc, making a few variables final that could be final
and incorporating the MATH885 changes (externalizing array argument checks) I also added
a few more tests.
I am still working on the TestUtils changes. Name change there will have to wait until 4.0
if we decide to do it. I am ambivalent, as the package name .inference is what you would
end up logically adding  i.e., InferenceTestUtils  but that would be redundant. I will
add a reference to Ted's paper and other discussion in the User Guide.
I am also wondering whether it may be better to make the entropy methods public and move them
to StatUtils.
> GTest (LogLikelihood ratio  LLR test) in math.stat.inference
> 
>
> Key: MATH878
> URL: https://issues.apache.org/jira/browse/MATH878
> Project: Commons Math
> Issue Type: New Feature
> Affects Versions: 3.1, 3.2, 4.0
> Environment: Netbeans
> Reporter: Radoslav Tsvetkov
> Labels: features, test
> Fix For: 3.1
>
> Attachments: MATH878_gTest_12102012.patch, MATH878_gTest_15102012.patch, MATH878_gTest_26102012.patch,
vcsdiff16294.patch
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> 1. Implementation of GTest (LogLikelihood ratio LLR test for independence and goodnesoffit)
> 2. Reference: http://en.wikipedia.org/wiki/Gtest
> 3. ReasonsUsefulness: Gtests are tests are increasingly being used in situations where
chisquared tests were previously recommended.
> The approximation to the theoretical chisquared distribution for the Gtest is better
than for the Pearson chisquared tests. In cases where Observed >2*Expected for some cell
case, the Gtest is always better than the chisquared test.
> For testing goodnessoffit the Gtest is infinitely more efficient than the chi squared
test in the sense of Bahadur, but the two tests are equally efficient in the sense of Pitman
or in the sense of Hodge and Lehman.

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